Levels.fyi Salary Data Report

Dataset statistics

Number of variables	17
Number of observations	62642
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	6.2 MiB
Average record size in memory	103.2 B

Variable types

DateTime	1
Categorical	8
Numeric	8

Alerts

`company` has a high cardinality: 1871 distinct values	High cardinality
`level` has a high cardinality: 3074 distinct values	High cardinality
`location` has a high cardinality: 1050 distinct values	High cardinality
`tag` has a high cardinality: 3276 distinct values	High cardinality
`otherdetails` has a high cardinality: 40133 distinct values	High cardinality
`dmaid` has a high cardinality: 150 distinct values	High cardinality
`totalyearlycompensation` is highly correlated with `basesalary` and 1 other fields	High correlation
`basesalary` is highly correlated with `totalyearlycompensation`	High correlation
`stockgrantvalue` is highly correlated with `totalyearlycompensation`	High correlation
`totalyearlycompensation` is highly correlated with `basesalary` and 2 other fields	High correlation
`basesalary` is highly correlated with `totalyearlycompensation`	High correlation
`stockgrantvalue` is highly correlated with `totalyearlycompensation`	High correlation
`bonus` is highly correlated with `totalyearlycompensation`	High correlation
`totalyearlycompensation` is highly correlated with `basesalary` and 1 other fields	High correlation
`basesalary` is highly correlated with `totalyearlycompensation`	High correlation
`stockgrantvalue` is highly correlated with `totalyearlycompensation`	High correlation
`totalyearlycompensation` is highly correlated with `basesalary` and 1 other fields	High correlation
`yearsofexperience` is highly correlated with `yearsatcompany`	High correlation
`yearsatcompany` is highly correlated with `yearsofexperience`	High correlation
`basesalary` is highly correlated with `totalyearlycompensation`	High correlation
`stockgrantvalue` is highly correlated with `totalyearlycompensation`	High correlation
`totalyearlycompensation` is highly skewed (γ1 = 32.04993004)	Skewed
`basesalary` is highly skewed (γ1 = 30.92064431)	Skewed
`stockgrantvalue` is highly skewed (γ1 = 64.07966542)	Skewed
`bonus` is highly skewed (γ1 = 36.90025253)	Skewed
`rowNumber` has unique values	Unique
`totalyearlycompensation` has 2297 (3.7%) zeros	Zeros
`yearsofexperience` has 4614 (7.4%) zeros	Zeros
`yearsatcompany` has 16203 (25.9%) zeros	Zeros
`basesalary` has 2304 (3.7%) zeros	Zeros
`stockgrantvalue` has 17181 (27.4%) zeros	Zeros
`bonus` has 15427 (24.6%) zeros	Zeros

Reproduction

Analysis started	2022-05-06 00:37:03.674282
Analysis finished	2022-05-06 00:38:44.162492
Duration	1 minute and 40.49 seconds
Software version	pandas-profiling v3.2.0
Download configuration	config.json

timestamp
Date

Distinct	62561
Distinct (%)	99.9%
Missing	0
Missing (%)	0.0%
Memory size	489.5 KiB

Minimum	2017-06-07 11:33:27
Maximum	2021-08-17 08:28:57

Histogram

Histogram with fixed size bins (bins=50)

company
Categorical

HIGH CARDINALITY

Distinct	1871
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Memory size	201.6 KiB

Amazon	8054
Microsoft	5162
Google	4313
Facebook	2962
Apple	2015
Other values (1866)	40136

Length

Max length	39
Median length	31
Mean length	7.653650905
Min length	2

Characters and Unicode

Total characters	479440
Distinct characters	71
Distinct categories	8 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	518 ?
Unique (%)	0.8%

Sample

1st row	Oracle
2nd row	eBay
3rd row	Amazon
4th row	Microsoft
5th row	Amazon

Common Values

Value	Count	Frequency (%)
Amazon	8054	12.9%
Microsoft	5162	8.2%
Google	4313	6.9%
Facebook	2962	4.7%
Apple	2015	3.2%
Oracle	1122	1.8%
Salesforce	1042	1.7%
Intel	941	1.5%
Cisco	901	1.4%
IBM	900	1.4%
Other values (1861)	35230	56.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
amazon	8225	11.4%
microsoft	5252	7.3%
google	4368	6.1%
facebook	3004	4.2%
apple	2057	2.9%
oracle	1143	1.6%
salesforce	1065	1.5%
intel	992	1.4%
cisco	959	1.3%
ibm	927	1.3%
Other values (1187)	44157	61.2%

Most occurring characters

Value	Count	Frequency (%)
o	54590	11.4%
e	38755	8.1%
a	37999	7.9%
n	25341	5.3%
r	24063	5.0%
i	23604	4.9%
l	22595	4.7%
t	22546	4.7%
c	19438	4.1%
s	18439	3.8%
Other values (61)	192070	40.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	383906	80.1%
Uppercase Letter	84399	17.6%
Space Separator	10111	2.1%
Other Punctuation	524	0.1%
Decimal Number	300	0.1%
Dash Punctuation	184	< 0.1%
Open Punctuation	8	< 0.1%
Close Punctuation	8	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	54590	14.2%
e	38755	10.1%
a	37999	9.9%
n	25341	6.6%
r	24063	6.3%
i	23604	6.1%
l	22595	5.9%
t	22546	5.9%
c	19438	5.1%
s	18439	4.8%
Other values (16)	96536	25.1%

Uppercase Letter

Value	Count	Frequency (%)
A	14920	17.7%
M	10004	11.9%
S	6729	8.0%
G	6420	7.6%
C	5359	6.3%
I	4392	5.2%
F	3890	4.6%
B	3807	4.5%
P	3435	4.1%
T	3022	3.6%
Other values (16)	22421	26.6%

Decimal Number

Value	Count	Frequency (%)
3	88	29.3%
1	52	17.3%
5	45	15.0%
2	41	13.7%
7	22	7.3%
6	20	6.7%
0	18	6.0%
8	14	4.7%

Other Punctuation

Value	Count	Frequency (%)
.	295	56.3%
&	141	26.9%
'	73	13.9%
,	5	1.0%
*	5	1.0%
/	5	1.0%

Space Separator

Value	Count	Frequency (%)
	10110	> 99.9%
	1	< 0.1%

Dash Punctuation

Value	Count	Frequency (%)
-	184	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	8	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	8	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	468305	97.7%
Common	11135	2.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	54590	11.7%
e	38755	8.3%
a	37999	8.1%
n	25341	5.4%
r	24063	5.1%
i	23604	5.0%
l	22595	4.8%
t	22546	4.8%
c	19438	4.2%
s	18439	3.9%
Other values (42)	180935	38.6%

Common

Value	Count	Frequency (%)
	10110	90.8%
.	295	2.6%
-	184	1.7%
&	141	1.3%
3	88	0.8%
'	73	0.7%
1	52	0.5%
5	45	0.4%
2	41	0.4%
7	22	0.2%
Other values (9)	84	0.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	479439	> 99.9%
None	1	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	54590	11.4%
e	38755	8.1%
a	37999	7.9%
n	25341	5.3%
r	24063	5.0%
i	23604	4.9%
l	22595	4.7%
t	22546	4.7%
c	19438	4.1%
s	18439	3.8%
Other values (60)	192069	40.1%

None

Value	Count	Frequency (%)
	1	100.0%

level
Categorical

HIGH CARDINALITY

Distinct	3074
Distinct (%)	4.9%
Missing	0
Missing (%)	0.0%
Memory size	211.0 KiB

L4	5008
L5	4861
L3	3331
L6	2866
Senior Software Engineer	1433
Other values (3069)	45143

Length

Max length	59
Median length	54
Mean length	5.904808276
Min length	1

Characters and Unicode

Total characters	369889
Distinct characters	101
Distinct categories	13 ?
Distinct scripts	4 ?
Distinct blocks	4 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1798 ?
Unique (%)	2.9%

Sample

1st row	L3
2nd row	SE 2
3rd row	L7
4th row	64
5th row	L5

Common Values

Value	Count	Frequency (%)
L4	5008	8.0%
L5	4861	7.8%
L3	3331	5.3%
L6	2866	4.6%
Senior Software Engineer	1433	2.3%
L2	1162	1.9%
Senior	1048	1.7%
L7	916	1.5%
L1	764	1.2%
62	764	1.2%
Other values (3064)	40489	64.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
engineer	6267	7.3%
senior	5702	6.6%
l4	5108	5.9%
l5	5035	5.8%
software	4952	5.7%
l3	3419	4.0%
l6	3286	3.8%
sde	1630	1.9%
staff	1601	1.9%
associate	1516	1.8%
Other values (1356)	47657	55.3%

Most occurring characters

Value	Count	Frequency (%)
e	35149	9.5%
n	25546	6.9%
r	25426	6.9%
	23967	6.5%
L	21638	5.8%
i	18781	5.1%
S	17487	4.7%
a	17118	4.6%
o	15205	4.1%
t	12983	3.5%
Other values (91)	156589	42.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	198285	53.6%
Uppercase Letter	92240	24.9%
Decimal Number	53357	14.4%
Space Separator	23967	6.5%
Dash Punctuation	1117	0.3%
Other Punctuation	410	0.1%
Close Punctuation	248	0.1%
Open Punctuation	248	0.1%
Math Symbol	8	< 0.1%
Modifier Symbol	4	< 0.1%
Other values (3)	5	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	35149	17.7%
n	25546	12.9%
r	25426	12.8%
i	18781	9.5%
a	17118	8.6%
o	15205	7.7%
t	12983	6.5%
g	8860	4.5%
f	8472	4.3%
s	5691	2.9%
Other values (31)	25054	12.6%

Uppercase Letter

Value	Count	Frequency (%)
L	21638	23.5%
S	17487	19.0%
E	12233	13.3%
I	9539	10.3%
C	5903	6.4%
T	4971	5.4%
M	4819	5.2%
P	3523	3.8%
D	3490	3.8%
A	2801	3.0%
Other values (19)	5836	6.3%

Decimal Number

Value	Count	Frequency (%)
6	9750	18.3%
4	9612	18.0%
5	9207	17.3%
3	8257	15.5%
2	5770	10.8%
1	4804	9.0%
7	2135	4.0%
0	1636	3.1%
9	1165	2.2%
8	1021	1.9%

Other Punctuation

Value	Count	Frequency (%)
/	204	49.8%
.	149	36.3%
,	28	6.8%
&	16	3.9%
?	6	1.5%
#	3	0.7%
:	2	0.5%
;	1	0.2%
\	1	0.2%

Dash Punctuation

Value	Count	Frequency (%)
-	1116	99.9%
–	1	0.1%

Math Symbol

Value	Count	Frequency (%)
\|	7	87.5%
+	1	12.5%

Other Letter

Value	Count	Frequency (%)
專	1	50.0%
員	1	50.0%

Space Separator

Value	Count	Frequency (%)
	23967	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	248	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	248	100.0%

Modifier Symbol

Value	Count	Frequency (%)
`	4	100.0%

Currency Symbol

Value	Count	Frequency (%)
$	2	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	290501	78.5%
Common	79362	21.5%
Cyrillic	24	< 0.1%
Han	2	< 0.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	35149	12.1%
n	25546	8.8%
r	25426	8.8%
L	21638	7.4%
i	18781	6.5%
S	17487	6.0%
a	17118	5.9%
o	15205	5.2%
t	12983	4.5%
E	12233	4.2%
Other values (42)	88935	30.6%

Common

Value	Count	Frequency (%)
	23967	30.2%
6	9750	12.3%
4	9612	12.1%
5	9207	11.6%
3	8257	10.4%
2	5770	7.3%
1	4804	6.1%
7	2135	2.7%
0	1636	2.1%
9	1165	1.5%
Other values (19)	3059	3.9%

Cyrillic

Value	Count	Frequency (%)
а	2	8.3%
л	2	8.3%
о	2	8.3%
в	2	8.3%
е	2	8.3%
и	2	8.3%
я	1	4.2%
р	1	4.2%
н	1	4.2%
п	1	4.2%
Other values (8)	8	33.3%

Han

Value	Count	Frequency (%)
專	1	50.0%
員	1	50.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	369862	> 99.9%
Cyrillic	24	< 0.1%
CJK	2	< 0.1%
Punctuation	1	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	35149	9.5%
n	25546	6.9%
r	25426	6.9%
	23967	6.5%
L	21638	5.9%
i	18781	5.1%
S	17487	4.7%
a	17118	4.6%
o	15205	4.1%
t	12983	3.5%
Other values (70)	156562	42.3%

Cyrillic

Value	Count	Frequency (%)
а	2	8.3%
л	2	8.3%
о	2	8.3%
в	2	8.3%
е	2	8.3%
и	2	8.3%
я	1	4.2%
р	1	4.2%
н	1	4.2%
п	1	4.2%
Other values (8)	8	33.3%

CJK

Value	Count	Frequency (%)
專	1	50.0%
員	1	50.0%

Punctuation

Value	Count	Frequency (%)
–	1	100.0%

title
Categorical

Distinct	15
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	489.5 KiB

Software Engineer	41231
Product Manager	4673
Software Engineering Manager	3569
Data Scientist	2578
Hardware Engineer	2200
Other values (10)	8391

Length

Max length	28
Median length	17
Mean length	17.34033077
Min length	5

Characters and Unicode

Total characters	1086233
Distinct characters	31
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Product Manager
2nd row	Software Engineer
3rd row	Product Manager
4th row	Software Engineering Manager
5th row	Software Engineer

Common Values

Value	Count	Frequency (%)
Software Engineer	41231	65.8%
Product Manager	4673	7.5%
Software Engineering Manager	3569	5.7%
Data Scientist	2578	4.1%
Hardware Engineer	2200	3.5%
Product Designer	1516	2.4%
Technical Program Manager	1381	2.2%
Solution Architect	1157	1.8%
Management Consultant	976	1.6%
Business Analyst	885	1.4%
Other values (5)	2476	4.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
software	44800	34.8%
engineer	43921	34.2%
manager	9623	7.5%
product	6189	4.8%
engineering	3569	2.8%
data	2578	2.0%
scientist	2578	2.0%
hardware	2200	1.7%
designer	1516	1.2%
technical	1381	1.1%
Other values (13)	10257	8.0%

Most occurring characters

Value	Count	Frequency (%)
e	165879	15.3%
n	122042	11.2%
r	119913	11.0%
a	82692	7.6%
t	67168	6.2%
	65970	6.1%
g	65265	6.0%
i	63962	5.9%
o	56024	5.2%
S	48996	4.5%
Other values (21)	228322	21.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	891651	82.1%
Uppercase Letter	128612	11.8%
Space Separator	65970	6.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	165879	18.6%
n	122042	13.7%
r	119913	13.4%
a	82692	9.3%
t	67168	7.5%
g	65265	7.3%
i	63962	7.2%
o	56024	6.3%
w	47000	5.3%
f	44800	5.0%
Other values (9)	56906	6.4%

Uppercase Letter

Value	Count	Frequency (%)
S	48996	38.1%
E	47490	36.9%
M	11799	9.2%
P	7570	5.9%
D	4094	3.2%
H	2564	2.0%
A	2042	1.6%
T	1381	1.1%
C	976	0.8%
B	885	0.7%

Space Separator

Value	Count	Frequency (%)
	65970	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1020263	93.9%
Common	65970	6.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	165879	16.3%
n	122042	12.0%
r	119913	11.8%
a	82692	8.1%
t	67168	6.6%
g	65265	6.4%
i	63962	6.3%
o	56024	5.5%
S	48996	4.8%
E	47490	4.7%
Other values (20)	180832	17.7%

Common

Value	Count	Frequency (%)
	65970	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1086233	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	165879	15.3%
n	122042	11.2%
r	119913	11.0%
a	82692	7.6%
t	67168	6.2%
	65970	6.1%
g	65265	6.0%
i	63962	5.9%
o	56024	5.2%
S	48996	4.5%
Other values (21)	228322	21.0%

totalyearlycompensation
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED
ZEROS

Distinct	1836
Distinct (%)	2.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3175.327065

Minimum	0
Maximum	3386013
Zeros	2297
Zeros (%)	3.7%
Negative	0
Negative (%)	0.0%
Memory size	489.5 KiB

Quantile statistics

Minimum	0
5-th percentile	27
Q1	116
median	183
Q3	269
95-th percentile	507
Maximum	3386013
Range	3386013
Interquartile range (IQR)	153

Descriptive statistics

Standard deviation	38778.77419
Coefficient of variation (CV)	12.2125291
Kurtosis	1799.206627
Mean	3175.327065
Median Absolute Deviation (MAD)	74
Skewness	32.04993004
Sum	198908838
Variance	1503793327
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	2297	3.7%
157	280	0.4%
129	268	0.4%
137	265	0.4%
148	263	0.4%
141	260	0.4%
143	259	0.4%
187	259	0.4%
151	257	0.4%
192	257	0.4%
Other values (1826)	57977	92.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	2297	3.7%
3	2	< 0.1%
4	1	< 0.1%
5	3	< 0.1%
6	5	< 0.1%
7	12	< 0.1%
8	23	< 0.1%
9	22	< 0.1%
10	32	0.1%
11	18	< 0.1%

Value	Count	Frequency (%)
3386013	1	< 0.1%
2593369	1	< 0.1%
2111744	1	< 0.1%
2057772	1	< 0.1%
1949865	1	< 0.1%
1242825	1	< 0.1%
1205904	1	< 0.1%
1162164	1	< 0.1%
1160132	1	< 0.1%
1115270	1	< 0.1%

location
Categorical

HIGH CARDINALITY

Distinct	1050
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Memory size	163.0 KiB

Seattle, WA	8701
San Francisco, CA	6797
New York, NY	4562
Redmond, WA	2649
Mountain View, CA	2275
Other values (1045)	37658

Length

Max length	41
Median length	38
Mean length	14.1890425
Min length	7

Characters and Unicode

Total characters	888830
Distinct characters	59
Distinct categories	7 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	402 ?
Unique (%)	0.6%

Sample

1st row	Redwood City, CA
2nd row	San Francisco, CA
3rd row	Seattle, WA
4th row	Redmond, WA
5th row	Vancouver, BC, Canada

Common Values

Value	Count	Frequency (%)
Seattle, WA	8701	13.9%
San Francisco, CA	6797	10.9%
New York, NY	4562	7.3%
Redmond, WA	2649	4.2%
Mountain View, CA	2275	3.6%
Sunnyvale, CA	2248	3.6%
San Jose, CA	2047	3.3%
Austin, TX	1527	2.4%
Menlo Park, CA	1440	2.3%
Cupertino, CA	1431	2.3%
Other values (1040)	28965	46.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
ca	22824	14.2%
wa	12356	7.7%
san	10169	6.3%
seattle	8701	5.4%
francisco	6823	4.2%
ny	4715	2.9%
new	4609	2.9%
york	4572	2.8%
india	2830	1.8%
tx	2702	1.7%
Other values (1267)	80556	50.1%

Most occurring characters

Value	Count	Frequency (%)
	98215	11.0%
,	72468	8.2%
a	69382	7.8%
n	63337	7.1%
e	55820	6.3%
o	47779	5.4%
A	46957	5.3%
t	37857	4.3%
i	33675	3.8%
C	33441	3.8%
Other values (49)	329899	37.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	494333	55.6%
Uppercase Letter	223573	25.2%
Space Separator	98215	11.0%
Other Punctuation	72537	8.2%
Dash Punctuation	110	< 0.1%
Open Punctuation	31	< 0.1%
Close Punctuation	31	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	69382	14.0%
n	63337	12.8%
e	55820	11.3%
o	47779	9.7%
t	37857	7.7%
i	33675	6.8%
l	30145	6.1%
r	29899	6.0%
s	20428	4.1%
d	19875	4.0%
Other values (16)	86136	17.4%

Uppercase Letter

Value	Count	Frequency (%)
A	46957	21.0%
C	33441	15.0%
S	25934	11.6%
N	14617	6.5%
W	13619	6.1%
Y	9558	4.3%
M	8742	3.9%
F	7882	3.5%
B	6524	2.9%
T	6189	2.8%
Other values (16)	50110	22.4%

Other Punctuation

Value	Count	Frequency (%)
,	72468	99.9%
.	67	0.1%
'	2	< 0.1%

Space Separator

Value	Count	Frequency (%)
	98215	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	110	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	31	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	31	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	717906	80.8%
Common	170924	19.2%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	69382	9.7%
n	63337	8.8%
e	55820	7.8%
o	47779	6.7%
A	46957	6.5%
t	37857	5.3%
i	33675	4.7%
C	33441	4.7%
l	30145	4.2%
r	29899	4.2%
Other values (42)	269614	37.6%

Common

Value	Count	Frequency (%)
	98215	57.5%
,	72468	42.4%
-	110	0.1%
.	67	< 0.1%
(	31	< 0.1%
)	31	< 0.1%
'	2	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	888830	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	98215	11.0%
,	72468	8.2%
a	69382	7.8%
n	63337	7.1%
e	55820	6.3%
o	47779	5.4%
A	46957	5.3%
t	37857	4.3%
i	33675	3.8%
C	33441	3.8%
Other values (49)	329899	37.1%

yearsofexperience
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	56
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	7.191053925

Minimum	0
Maximum	90
Zeros	4614
Zeros (%)	7.4%
Negative	0
Negative (%)	0.0%
Memory size	489.5 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	3
median	6
Q3	10
95-th percentile	20
Maximum	90
Range	90
Interquartile range (IQR)	7

Descriptive statistics

Standard deviation	6.437148272
Coefficient of variation (CV)	0.8951606174
Kurtosis	3.40735208
Mean	7.191053925
Median Absolute Deviation (MAD)	4
Skewness	1.536440913
Sum	450462
Variance	41.43687787
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
3	6413	10.2%
1	5937	9.5%
4	5430	8.7%
2	4683	7.5%
0	4614	7.4%
6	4555	7.3%
5	4236	6.8%
7	3768	6.0%
9	2918	4.7%
8	2796	4.5%
Other values (46)	17292	27.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	4614	7.4%
1	5937	9.5%
2	4683	7.5%
3	6413	10.2%
4	5430	8.7%
5	4236	6.8%
6	4555	7.3%
7	3768	6.0%
8	2796	4.5%
9	2918	4.7%

Value	Count	Frequency (%)
90	1	< 0.1%
58	1	< 0.1%
57	3	< 0.1%
53	2	< 0.1%
51	2	< 0.1%
50	2	< 0.1%
49	3	< 0.1%
48	5	< 0.1%
47	2	< 0.1%
46	1	< 0.1%

yearsatcompany
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	44
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.7006162

Minimum	0
Maximum	90
Zeros	16203
Zeros (%)	25.9%
Negative	0
Negative (%)	0.0%
Memory size	489.5 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	4
95-th percentile	9
Maximum	90
Range	90
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	3.524030209
Coefficient of variation (CV)	1.304898567
Kurtosis	17.45339846
Mean	2.7006162
Median Absolute Deviation (MAD)	1
Skewness	2.973821206
Sum	169172
Variance	12.41878891
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=44)

Value	Count	Frequency (%)
0	16203	25.9%
1	15545	24.8%
3	7821	12.5%
2	6885	11.0%
4	4667	7.5%
6	2549	4.1%
5	2467	3.9%
7	1677	2.7%
9	931	1.5%
8	893	1.4%
Other values (34)	3004	4.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	16203	25.9%
1	15545	24.8%
2	6885	11.0%
3	7821	12.5%
4	4667	7.5%
5	2467	3.9%
6	2549	4.1%
7	1677	2.7%
8	893	1.4%
9	931	1.5%

Value	Count	Frequency (%)
90	1	< 0.1%
47	1	< 0.1%
43	1	< 0.1%
42	1	< 0.1%
39	1	< 0.1%
38	1	< 0.1%
37	2	< 0.1%
36	2	< 0.1%
35	2	< 0.1%
34	1	< 0.1%

tag
Categorical

HIGH CARDINALITY

Distinct	3276
Distinct (%)	5.2%
Missing	0
Missing (%)	0.0%
Memory size	489.5 KiB

Full Stack	11382
Distributed Systems (Back-End)	10838
API Development (Back-End)	6277
ML / AI	4204
Web Development (Front-End)	2971
Other values (3271)	26970

Length

Max length	84
Median length	59
Mean length	15.5467418
Min length	0

Characters and Unicode

Total characters	973879
Distinct characters	80
Distinct categories	9 ?
Distinct scripts	2 ?
Distinct blocks	3 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2378 ?
Unique (%)	3.8%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

Value	Count	Frequency (%)
Full Stack	11382	18.2%
Distributed Systems (Back-End)	10838	17.3%
API Development (Back-End)	6277	10.0%
ML / AI	4204	6.7%
Web Development (Front-End)	2971	4.7%
Product	1791	2.9%
Data	1580	2.5%
DevOps	1573	2.5%
Security	1197	1.9%
Networking	1178	1.9%
Other values (3266)	19651	31.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
back-end	17131	12.8%
full	11388	8.5%
stack	11388	8.5%
systems	11130	8.3%
distributed	10840	8.1%
development	9426	7.1%
api	6281	4.7%
	5270	3.9%
ml	4275	3.2%
ai	4238	3.2%
Other values (1459)	42121	31.6%

Most occurring characters

Value	Count	Frequency (%)
e	77924	8.0%
	72275	7.4%
t	72224	7.4%
n	48374	5.0%
i	43041	4.4%
a	42330	4.3%
s	42010	4.3%
d	40490	4.2%
l	39734	4.1%
c	38353	3.9%
Other values (70)	457124	46.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	649243	66.7%
Uppercase Letter	179849	18.5%
Space Separator	72276	7.4%
Open Punctuation	23264	2.4%
Close Punctuation	23263	2.4%
Dash Punctuation	20162	2.1%
Other Punctuation	4758	0.5%
Math Symbol	990	0.1%
Decimal Number	74	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	77924	12.0%
t	72224	11.1%
n	48374	7.5%
i	43041	6.6%
a	42330	6.5%
s	42010	6.5%
d	40490	6.2%
l	39734	6.1%
c	38353	5.9%
r	30735	4.7%
Other values (17)	174028	26.8%

Uppercase Letter

Value	Count	Frequency (%)
S	30330	16.9%
D	25856	14.4%
E	23818	13.2%
B	17496	9.7%
F	14724	8.2%
A	14513	8.1%
I	11653	6.5%
P	9705	5.4%
M	6255	3.5%
L	4581	2.5%
Other values (17)	20918	11.6%

Other Punctuation

Value	Count	Frequency (%)
/	4449	93.5%
,	160	3.4%
&	119	2.5%
.	14	0.3%
;	5	0.1%
?	4	0.1%
#	2	< 0.1%
@	2	< 0.1%
'	2	< 0.1%
:	1	< 0.1%

Decimal Number

Value	Count	Frequency (%)
5	21	28.4%
2	18	24.3%
3	10	13.5%
6	9	12.2%
1	7	9.5%
4	4	5.4%
0	4	5.4%
8	1	1.4%

Math Symbol

Value	Count	Frequency (%)
+	987	99.7%
>	2	0.2%
\|	1	0.1%

Space Separator

Value	Count	Frequency (%)
	72275	> 99.9%
	1	< 0.1%

Open Punctuation

Value	Count	Frequency (%)
(	23264	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	23263	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	20162	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	829092	85.1%
Common	144787	14.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	77924	9.4%
t	72224	8.7%
n	48374	5.8%
i	43041	5.2%
a	42330	5.1%
s	42010	5.1%
d	40490	4.9%
l	39734	4.8%
c	38353	4.6%
r	30735	3.7%
Other values (44)	353877	42.7%

Common

Value	Count	Frequency (%)
	72275	49.9%
(	23264	16.1%
)	23263	16.1%
-	20162	13.9%
/	4449	3.1%
+	987	0.7%
,	160	0.1%
&	119	0.1%
5	21	< 0.1%
2	18	< 0.1%
Other values (16)	69	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	973876	> 99.9%
None	2	< 0.1%
Punctuation	1	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	77924	8.0%
	72275	7.4%
t	72224	7.4%
n	48374	5.0%
i	43041	4.4%
a	42330	4.3%
s	42010	4.3%
d	40490	4.2%
l	39734	4.1%
c	38353	3.9%
Other values (67)	457121	46.9%

None

Value	Count	Frequency (%)
ł	1	50.0%
È	1	50.0%

Punctuation

Value	Count	Frequency (%)
	1	100.0%

basesalary
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED
ZEROS

Distinct	1263
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1798.144663

Minimum	0
Maximum	2057772
Zeros	2304
Zeros (%)	3.7%
Negative	0
Negative (%)	0.0%
Memory size	489.5 KiB

Quantile statistics

Minimum	0
5-th percentile	21
Q1	88
median	131
Q3	181
95-th percentile	270
Maximum	2057772
Range	2057772
Interquartile range (IQR)	93

Descriptive statistics

Standard deviation	19271.93695
Coefficient of variation (CV)	10.71767881
Kurtosis	2355.55225
Mean	1798.144663
Median Absolute Deviation (MAD)	46
Skewness	30.92064431
Sum	112639378
Variance	371407553.9
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	2304	3.7%
105	437	0.7%
112	407	0.6%
115	404	0.6%
111	398	0.6%
94	391	0.6%
95	390	0.6%
96	390	0.6%
104	388	0.6%
117	387	0.6%
Other values (1253)	56746	90.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	2304	3.7%
1	1	< 0.1%
3	6	< 0.1%
4	2	< 0.1%
5	4	< 0.1%
6	17	< 0.1%
7	15	< 0.1%
8	24	< 0.1%
9	31	< 0.1%
10	49	0.1%

Value	Count	Frequency (%)
2057772	1	< 0.1%
1098310	1	< 0.1%
560740	1	< 0.1%
556416	1	< 0.1%
537732	1	< 0.1%
535462	1	< 0.1%
451883	1	< 0.1%
368829	1	< 0.1%
358689	1	< 0.1%
357078	1	< 0.1%

stockgrantvalue
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED
ZEROS

Distinct	1281
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1134.865202

Minimum	0
Maximum	3140803
Zeros	17181
Zeros (%)	27.4%
Negative	0
Negative (%)	0.0%
Memory size	489.5 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	23
Q3	64
95-th percentile	226
Maximum	3140803
Range	3140803
Interquartile range (IQR)	64

Descriptive statistics

Standard deviation	25206.11464
Coefficient of variation (CV)	22.21066836
Kurtosis	5985.821437
Mean	1134.865202
Median Absolute Deviation (MAD)	23
Skewness	64.07966542
Sum	71090226
Variance	635348215.1
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	17181	27.4%
6	759	1.2%
15	731	1.2%
4	722	1.2%
3	715	1.1%
13	702	1.1%
10	701	1.1%
14	700	1.1%
7	687	1.1%
5	677	1.1%
Other values (1271)	39067	62.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	17181	27.4%
1	501	0.8%
2	453	0.7%
3	715	1.1%
4	722	1.2%
5	677	1.1%
6	759	1.2%
7	687	1.1%
8	567	0.9%
9	665	1.1%

Value	Count	Frequency (%)
3140803	1	< 0.1%
2296728	1	< 0.1%
1860458	1	< 0.1%
1581036	1	< 0.1%
1076085	1	< 0.1%
1055359	1	< 0.1%
998780	1	< 0.1%
952489	1	< 0.1%
907808	1	< 0.1%
872514	1	< 0.1%

bonus
Real number (ℝ_≥0)

HIGH CORRELATION
SKEWED
ZEROS

Distinct	812
Distinct (%)	1.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	242.3171993

Minimum	0
Maximum	384026
Zeros	15427
Zeros (%)	24.6%
Negative	0
Negative (%)	0.0%
Memory size	489.5 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	13
Q3	27
95-th percentile	67
Maximum	384026
Range	384026
Interquartile range (IQR)	26

Descriptive statistics

Standard deviation	3709.187697
Coefficient of variation (CV)	15.30715817
Kurtosis	2422.19552
Mean	242.3171993
Median Absolute Deviation (MAD)	13
Skewness	36.90025253
Sum	15179234
Variance	13758073.37
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	15427	24.6%
15	1589	2.5%
10	1532	2.4%
12	1515	2.4%
14	1492	2.4%
7	1487	2.4%
13	1483	2.4%
11	1480	2.4%
9	1461	2.3%
6	1456	2.3%
Other values (802)	33720	53.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	15427	24.6%
1	864	1.4%
2	748	1.2%
3	1253	2.0%
4	1123	1.8%
5	1301	2.1%
6	1456	2.3%
7	1487	2.4%
8	1316	2.1%
9	1461	2.3%

Value	Count	Frequency (%)
384026	1	< 0.1%
180704	1	< 0.1%
158966	1	< 0.1%
158458	1	< 0.1%
153649	1	< 0.1%
151540	1	< 0.1%
147308	1	< 0.1%
140752	1	< 0.1%
130713	1	< 0.1%
116638	1	< 0.1%

gender
Categorical

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	61.5 KiB

Male	35702
	19540
Female	6999
Other	400
Title: Senior Software Engineer	1

Length

Max length	31
Median length	4
Mean length	2.982551643
Min length	0

Characters and Unicode

Total characters	186833
Distinct characters	21
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

Value	Count	Frequency (%)
Male	35702	57.0%
	19540	31.2%
Female	6999	11.2%
Other	400	0.6%
Title: Senior Software Engineer	1	< 0.1%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
male	35702	82.8%
female	6999	16.2%
other	400	0.9%
title	1	< 0.1%
senior	1	< 0.1%
software	1	< 0.1%
engineer	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
e	50105	26.8%
l	42702	22.9%
a	42702	22.9%
M	35702	19.1%
F	6999	3.7%
m	6999	3.7%
r	403	0.2%
t	402	0.2%
h	400	0.2%
O	400	0.2%
Other values (11)	19	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	143724	76.9%
Uppercase Letter	43105	23.1%
Space Separator	3	< 0.1%
Other Punctuation	1	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	50105	34.9%
l	42702	29.7%
a	42702	29.7%
m	6999	4.9%
r	403	0.3%
t	402	0.3%
h	400	0.3%
i	3	< 0.1%
n	3	< 0.1%
o	2	< 0.1%
Other values (3)	3	< 0.1%

Uppercase Letter

Value	Count	Frequency (%)
M	35702	82.8%
F	6999	16.2%
O	400	0.9%
S	2	< 0.1%
E	1	< 0.1%
T	1	< 0.1%

Space Separator

Value	Count	Frequency (%)
	3	100.0%

Other Punctuation

Value	Count	Frequency (%)
:	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	186829	> 99.9%
Common	4	< 0.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	50105	26.8%
l	42702	22.9%
a	42702	22.9%
M	35702	19.1%
F	6999	3.7%
m	6999	3.7%
r	403	0.2%
t	402	0.2%
h	400	0.2%
O	400	0.2%
Other values (9)	15	< 0.1%

Common

Value	Count	Frequency (%)
	3	75.0%
:	1	25.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	186833	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	50105	26.8%
l	42702	22.9%
a	42702	22.9%
M	35702	19.1%
F	6999	3.7%
m	6999	3.7%
r	403	0.2%
t	402	0.2%
h	400	0.2%
O	400	0.2%
Other values (11)	19	< 0.1%

otherdetails
Categorical

HIGH CARDINALITY

Distinct	40133
Distinct (%)	64.1%
Missing	0
Missing (%)	0.0%
Memory size	489.5 KiB

	22503
freaun	2
braiock	2
schnuolls	2
twauesly	2
Other values (40128)	40131

Length

Max length	130
Median length	109
Mean length	37.61950449
Min length	0

Characters and Unicode

Total characters	2356561
Distinct characters	27
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	40125 ?
Unique (%)	64.1%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

Value	Count	Frequency (%)
	22503	35.9%
freaun	2	< 0.1%
braiock	2	< 0.1%
schnuolls	2	< 0.1%
twauesly	2	< 0.1%
whuott	2	< 0.1%
noilly	2	< 0.1%
cyclieuns	2	< 0.1%
glaarn qef spraak pleosk chielt shruith thiudly mcgian srieuk sziogh keedy	1	< 0.1%
mccoomp physieusts gritt kwiads froary swiesm kleirst daap hypeetch dynaiarty tadly	1	< 0.1%
Other values (40123)	40123	64.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
prioucts	8	< 0.1%
mcnaiards	8	< 0.1%
theauny	8	< 0.1%
hyiump	7	< 0.1%
mcfaiats	7	< 0.1%
bleady	7	< 0.1%
pliurds	7	< 0.1%
meesly	7	< 0.1%
vuids	6	< 0.1%
czihn	6	< 0.1%
Other values (219162)	321111	> 99.9%

Most occurring characters

Value	Count	Frequency (%)
	281043	11.9%
s	204363	8.7%
i	157021	6.7%
a	156293	6.6%
c	135613	5.8%
r	134123	5.7%
e	131501	5.6%
o	123409	5.2%
u	115832	4.9%
h	113294	4.8%
Other values (17)	804069	34.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	2075518	88.1%
Space Separator	281043	11.9%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
s	204363	9.8%
i	157021	7.6%
a	156293	7.5%
c	135613	6.5%
r	134123	6.5%
e	131501	6.3%
o	123409	5.9%
u	115832	5.6%
h	113294	5.5%
t	113211	5.5%
Other values (16)	690858	33.3%

Space Separator

Value	Count	Frequency (%)
	281043	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	2075518	88.1%
Common	281043	11.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
s	204363	9.8%
i	157021	7.6%
a	156293	7.5%
c	135613	6.5%
r	134123	6.5%
e	131501	6.3%
o	123409	5.9%
u	115832	5.6%
h	113294	5.5%
t	113211	5.5%
Other values (16)	690858	33.3%

Common

Value	Count	Frequency (%)
	281043	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2356561	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	281043	11.9%
s	204363	8.7%
i	157021	6.7%
a	156293	6.6%
c	135613	5.8%
r	134123	5.7%
e	131501	5.6%
o	123409	5.2%
u	115832	4.9%
h	113294	4.8%
Other values (17)	804069	34.1%

cityid
Real number (ℝ_≥0)

Distinct	1045
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	9856.201989

Minimum	0
Maximum	47926
Zeros	2
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	489.5 KiB

Quantile statistics

Minimum	0
5-th percentile	3663
Q1	7369
median	7839
Q3	11521
95-th percentile	15555
Maximum	47926
Range	47926
Interquartile range (IQR)	4152

Descriptive statistics

Standard deviation	6679.104563
Coefficient of variation (CV)	0.6776550004
Kurtosis	16.79525351
Mean	9856.201989
Median Absolute Deviation (MAD)	2343
Skewness	3.809126395
Sum	617412205
Variance	44610437.76
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
11527	8701	13.9%
7419	6796	10.8%
10182	4562	7.3%
11521	2649	4.2%
7322	2275	3.6%
7472	2246	3.6%
7422	2047	3.3%
10965	1527	2.4%
7300	1440	2.3%
7158	1431	2.3%
Other values (1035)	28968	46.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	2	< 0.1%
10	1	< 0.1%
1153	5	< 0.1%
1180	101	0.2%
1182	124	0.2%
1205	9	< 0.1%
1206	742	1.2%
1211	8	< 0.1%
1221	3	< 0.1%
1222	8	< 0.1%

Value	Count	Frequency (%)
47926	406	0.6%
47913	6	< 0.1%
47618	2	< 0.1%
42909	5	< 0.1%
42903	10	< 0.1%
42896	4	< 0.1%
42877	10	< 0.1%
42761	3	< 0.1%
42631	88	0.1%
42624	1	< 0.1%

dmaid
Categorical

HIGH CARDINALITY

Distinct	150
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	127.7 KiB

807	20400
819	12343
0	9826
501	5156
506	1773
Other values (145)	13144

Length

Max length	3
Median length	3
Mean length	2.686184988
Min length	0

Characters and Unicode

Total characters	168268
Distinct characters	10
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	26 ?
Unique (%)	< 0.1%

Sample

1st row	807
2nd row	807
3rd row	819
4th row	819
5th row	0

Common Values

Value	Count	Frequency (%)
807	20400	32.6%
819	12343	19.7%
0	9826	15.7%
501	5156	8.2%
506	1773	2.8%
635	1556	2.5%
511	1374	2.2%
803	1342	2.1%
825	854	1.4%
602	843	1.3%
Other values (140)	7175	11.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
807	20400	32.6%
819	12343	19.7%
0	9826	15.7%
501	5156	8.2%
506	1773	2.8%
635	1556	2.5%
511	1374	2.2%
803	1342	2.1%
825	854	1.4%
602	843	1.3%
Other values (139)	7173	11.5%

Most occurring characters

Value	Count	Frequency (%)
0	41568	24.7%
8	36508	21.7%
7	22393	13.3%
1	22051	13.1%
5	15336	9.1%
9	12800	7.6%
6	7274	4.3%
3	4777	2.8%
2	4338	2.6%
4	1223	0.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	168268	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	41568	24.7%
8	36508	21.7%
7	22393	13.3%
1	22051	13.1%
5	15336	9.1%
9	12800	7.6%
6	7274	4.3%
3	4777	2.8%
2	4338	2.6%
4	1223	0.7%

Most occurring scripts

Value	Count	Frequency (%)
Common	168268	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	41568	24.7%
8	36508	21.7%
7	22393	13.3%
1	22051	13.1%
5	15336	9.1%
9	12800	7.6%
6	7274	4.3%
3	4777	2.8%
2	4338	2.6%
4	1223	0.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	168268	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	41568	24.7%
8	36508	21.7%
7	22393	13.3%
1	22051	13.1%
5	15336	9.1%
9	12800	7.6%
6	7274	4.3%
3	4777	2.8%
2	4338	2.6%
4	1223	0.7%

rowNumber
Real number (ℝ_≥0)

UNIQUE

Distinct	62642
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	41694.72373

Minimum	1
Maximum	83875
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	489.5 KiB

Quantile statistics

Minimum	1
5-th percentile	3629.1
Q1	20069.25
median	42019
Q3	63021.75
95-th percentile	79529.95
Maximum	83875
Range	83874
Interquartile range (IQR)	42952.5

Descriptive statistics

Standard deviation	24488.86588
Coefficient of variation (CV)	0.587337286
Kurtosis	-1.225414232
Mean	41694.72373
Median Absolute Deviation (MAD)	21449.5
Skewness	-0.01475390822
Sum	2611840884
Variance	599704552
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	1	< 0.1%
56189	1	< 0.1%
56191	1	< 0.1%
56192	1	< 0.1%
56194	1	< 0.1%
56195	1	< 0.1%
56196	1	< 0.1%
56197	1	< 0.1%
56198	1	< 0.1%
56199	1	< 0.1%
Other values (62632)	62632	> 99.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	1	< 0.1%
2	1	< 0.1%
3	1	< 0.1%
5	1	< 0.1%
6	1	< 0.1%
7	1	< 0.1%
9	1	< 0.1%
10	1	< 0.1%
11	1	< 0.1%
12	1	< 0.1%

Value	Count	Frequency (%)
83875	1	< 0.1%
83874	1	< 0.1%
83872	1	< 0.1%
83871	1	< 0.1%
83870	1	< 0.1%
83867	1	< 0.1%
83865	1	< 0.1%
83863	1	< 0.1%
83861	1	< 0.1%
83858	1	< 0.1%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	timestamp	company	level	title	totalyearlycompensation	location	yearsofexperience	yearsatcompany	basesalary	stockgrantvalue	bonus	cityid	dmaid	rowNumber
0	2017-06-07 11:33:27	Oracle	L3	Product Manager	186	Redwood City, CA	1	1	160	17	9	7392	807	1
1	2017-06-10 17:11:29	eBay	SE 2	Software Engineer	0	San Francisco, CA	3	4	0	0	0	7419	807	2
2	2017-06-11 14:53:57	Amazon	L7	Product Manager	126	Seattle, WA	10	0	126	0	0	11527	819	3
3	2017-06-14 21:22:25	Microsoft	64	Software Engineering Manager	171348	Redmond, WA	13	13	92799	55371	23178	11521	819	5
4	2017-06-16 10:44:01	Amazon	L5	Software Engineer	214175	Vancouver, BC, Canada	13	1	156335	0	57840	1320	0	6
5	2017-06-17 00:23:14	Apple	M1	Software Engineering Manager	423	Sunnyvale, CA	6	6	157	219	47	7472	807	7
6	2017-06-20 10:58:51	Microsoft	60	Software Engineer	0	Mountain View, CA	7	2	0	0	0	7322	807	9
7	2017-06-20 18:49:59	Amazon	L5	Software Engineer	153939	Seattle, WA	3	3	101828	52111	0	11527	819	10
8	2017-06-21 17:27:47	Microsoft	63	Software Engineer	0	Seattle, WA	7	11	0	0	0	11527	819	11
9	2017-06-22 12:37:51	Microsoft	65	Software Engineering Manager	302	Redmond, WA	16	13	192	61	49	11521	819	12

Last rows

	timestamp	company	level	title	totalyearlycompensation	location	yearsofexperience	yearsatcompany	tag	basesalary	stockgrantvalue	bonus	gender	otherdetails	cityid	dmaid	rowNumber
62632	2021-08-17 05:57:34	Refinitiv	N/A	Product Manager	125	New York, NY	4	3	Product	97	0	28		schwocy prieurn	10182	501	83858
62633	2021-08-17 06:47:07	NCR	10	Software Engineer	113	Atlanta, GA	3	2	Full Stack	113	0	0	Male	leerf suorth kroesch vaapt hypiups symbioub hypuny saiong physiosts dynaiads sciil scroably treagy fiaold	7839	524	83861
62634	2021-08-17 07:15:05	Deloitte	Manager	Product Manager	230	Washington, DC	5	0	Product	190	0	40		dweiass plaany typuatts schriiks spriell swoals syniefy mcgeauv claury graond preath dynuentz slauecks	40303	511	83863
62635	2021-08-17 07:50:25	Raytheon Technologies	P2	Software Engineer	125	Portsmouth, RI	4	2	Distributed Systems (Back-End)	122	0	3	Male	szes skauns frairt struisly krauerr pfurf bloold bluesh sqiofy	35382	521	83865
62636	2021-08-17 07:55:47	AT&T	Principal	Data Scientist	229	Atlanta, GA	7	4	general	214	0	15		keuny twiintz scriitt scoiaz rhaub soob wheiapp spof xeult schotz	7839	524	83867
62637	2021-08-17 08:16:36	Amazon	L6	Product Manager	272	Seattle, WA	7	0	Analytic	176	51	45	Female	scrielt schwists fuech xauem typaiarty siids qiaongs throiak dynound twaiarty hypeuld	11527	819	83870
62638	2021-08-17 08:22:17	Fidelity Investments	L3	Software Engineer	50	Durham, NC	0	0	Full Stack	43	0	7	Male	pauss jiusts liaop rhiitts proing smiodly spluiel clids spiun knaiarth cycleorn theops	9606	560	83871
62639	2021-08-17 08:24:56	Cisco	Grade 8	Software Engineer	200	San Jose, CA	3	6	Networking	179	7	14	Male	triasm froidy peusk juieck skaorr	7422	807	83872
62640	2021-08-17 08:26:21	HSBC	GCB5	Software Engineer	86	New York, NY	10	5	Full Stack	72	0	14		hypoiarly khoiarts krol sqierg	10182	501	83874
62641	2021-08-17 08:28:57	Adobe	Software Engineer 5	Product Designer	382	San Francisco, CA	7	0	User Experience (UX)	230	139	13	Male	fluingly toasly croesm fiuk gniosk khaiarts strucy	7419	807	83875

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Decimal Number

Other Punctuation

Space Separator

Dash Punctuation

Open Punctuation

Close Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

None

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Decimal Number

Other Punctuation

Dash Punctuation

Math Symbol

Other Letter

Space Separator

Close Punctuation

Open Punctuation

Modifier Symbol

Currency Symbol

Connector Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Cyrillic

Han

Most occurring blocks

Most frequent character per block

ASCII

Cyrillic

CJK

Punctuation

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Other Punctuation

Space Separator

Dash Punctuation

Open Punctuation

Close Punctuation